Sistem Penilaian Mahasiswa Terhadap Fasilitas Kampus Politeknik Negeri Lhokseumawe Menggunakan Natural Language Processing
| Main Authors: | Icshan, Muhammad, Huzaeni, Huzaeni, Amirullah, Amirullah |
|---|---|
| Format: | Article info application/pdf Journal |
| Bahasa: | ind |
| Terbitan: |
Politeknik Negeri Lhokseumawe
, 2024
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| Online Access: |
http://e-jurnal.pnl.ac.id/JAISE/article/view/5404 http://e-jurnal.pnl.ac.id/JAISE/article/view/5404/3854 |
| ctrlnum |
article-5404 |
|---|---|
| fullrecord |
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<dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><title lang="id-ID">Sistem Penilaian Mahasiswa Terhadap Fasilitas Kampus Politeknik Negeri Lhokseumawe Menggunakan Natural Language Processing</title><creator>Icshan, Muhammad</creator><creator>Huzaeni, Huzaeni</creator><creator>Amirullah, Amirullah</creator><description lang="id-ID">Fasilitas, sebagai elemen pendukung dalam pelaksanaan tugas dan kegiatan, mendefinisikan sarana serta prasarana yang esensial untuk menunjang aktivitas suatu institusi. Studi ini dilakukan di Politeknik Negeri Lhokseumawe (PNL), di mana mahasiswa partisipan diminta untuk mengevaluasi fasilitas kampus melalui kuesioner Google. Kuesioner ini menyajikan 15 pertanyaan yang dapat diakses melalui tautan formulir kuesioner, mencakup aspek-aspek seperti ruang kelas, laboratorium, perabot belajar, peralatan pengajaran, dan layanan perpustakaan hingga teknologi e-learning. Saat ini, belum ada metode formal untuk mengklasifikasikan pandangan mahasiswa terhadap fasilitas kampus. Oleh karena itu, diperkenalkan metode klasifikasi sentimen dengan menggunakan Natural Language Processing (NLP) untuk membersihkan dan mengolah data teks. Setelah itu, data tersebut dimasukkan ke dalam model klasifikasi menggunakan Multi-layer Perceptron, yang mampu memberikan prediksi akurasi sebesar 80% berdasarkan 78 responden yang berpartisipasi dalam penelitian ini. Skenario eksperimen melibatkan 1023 data latih dan 105 data uji, termasuk ekstraksi fitur opini, menunjukkan bahwa model klasifikasi ini efektif dalam mengelola data berukuran besar dan kompleks. Abstract Facilities, as a supporting element in the implementation of tasks and activities, define the facilities and infrastructure that are essential to support the activities of an institution. This study was conducted at Politeknik Negeri Lhokseumawe (PNL), where participating students were asked to evaluate campus facilities through a Google questionnaire. The questionnaire presents 15 questions that can be accessed through the questionnaire form link, covering aspects such as classrooms, laboratories, learning furniture, teaching equipment, and library services to e-learning technology. Currently, there is no formal method to classify students' views on campus facilities. Therefore, a sentiment classification method is introduced by using Natural Language Processing (NLP) to clean and process the text data. Afterwards, the data was fed into a classification model using Multi-layer Perceptron, which was able to provide a prediction accuracy of 80% based on 78 respondents who participated in the study. Experimental scenarios involving 1023 training data and 105 test data, including opinion feature extraction, show that this classification model is effective in managing large and complex data.</description><publisher lang="id-ID">Politeknik Negeri Lhokseumawe</publisher><contributor lang="id-ID"/><date>2024-06-09</date><type>Journal:Article</type><type>Other:info:eu-repo/semantics/publishedVersion</type><type>Journal:Article</type><type>File:application/pdf</type><identifier>http://e-jurnal.pnl.ac.id/JAISE/article/view/5404</identifier><identifier>10.30811/jaise.v4i1.5404</identifier><source lang="en-US">Journal of Artificial Intelligence and Software Engineering; Vol 4, No 1 (2024); 48-54</source><source lang="id-ID">Journal of Artificial Intelligence and Software Engineering; Vol 4, No 1 (2024); 48-54</source><source>2777-001X</source><source>2797-054X</source><source>10.30811/jaise.v4i1</source><language>ind</language><relation>http://e-jurnal.pnl.ac.id/JAISE/article/view/5404/3854</relation><rights lang="id-ID">##submission.copyrightStatement##</rights><recordID>article-5404</recordID></dc>
|
| language |
ind |
| format |
Journal:Article Journal Other:info:eu-repo/semantics/publishedVersion Other File:application/pdf File Journal:Journal |
| author |
Icshan, Muhammad Huzaeni, Huzaeni Amirullah, Amirullah |
| title |
Sistem Penilaian Mahasiswa Terhadap Fasilitas Kampus Politeknik Negeri Lhokseumawe Menggunakan Natural Language Processing |
| publisher |
Politeknik Negeri Lhokseumawe |
| publishDate |
2024 |
| url |
http://e-jurnal.pnl.ac.id/JAISE/article/view/5404 http://e-jurnal.pnl.ac.id/JAISE/article/view/5404/3854 |
| contents |
Fasilitas, sebagai elemen pendukung dalam pelaksanaan tugas dan kegiatan, mendefinisikan sarana serta prasarana yang esensial untuk menunjang aktivitas suatu institusi. Studi ini dilakukan di Politeknik Negeri Lhokseumawe (PNL), di mana mahasiswa partisipan diminta untuk mengevaluasi fasilitas kampus melalui kuesioner Google. Kuesioner ini menyajikan 15 pertanyaan yang dapat diakses melalui tautan formulir kuesioner, mencakup aspek-aspek seperti ruang kelas, laboratorium, perabot belajar, peralatan pengajaran, dan layanan perpustakaan hingga teknologi e-learning. Saat ini, belum ada metode formal untuk mengklasifikasikan pandangan mahasiswa terhadap fasilitas kampus. Oleh karena itu, diperkenalkan metode klasifikasi sentimen dengan menggunakan Natural Language Processing (NLP) untuk membersihkan dan mengolah data teks. Setelah itu, data tersebut dimasukkan ke dalam model klasifikasi menggunakan Multi-layer Perceptron, yang mampu memberikan prediksi akurasi sebesar 80% berdasarkan 78 responden yang berpartisipasi dalam penelitian ini. Skenario eksperimen melibatkan 1023 data latih dan 105 data uji, termasuk ekstraksi fitur opini, menunjukkan bahwa model klasifikasi ini efektif dalam mengelola data berukuran besar dan kompleks. Abstract Facilities, as a supporting element in the implementation of tasks and activities, define the facilities and infrastructure that are essential to support the activities of an institution. This study was conducted at Politeknik Negeri Lhokseumawe (PNL), where participating students were asked to evaluate campus facilities through a Google questionnaire. The questionnaire presents 15 questions that can be accessed through the questionnaire form link, covering aspects such as classrooms, laboratories, learning furniture, teaching equipment, and library services to e-learning technology. Currently, there is no formal method to classify students' views on campus facilities. Therefore, a sentiment classification method is introduced by using Natural Language Processing (NLP) to clean and process the text data. Afterwards, the data was fed into a classification model using Multi-layer Perceptron, which was able to provide a prediction accuracy of 80% based on 78 respondents who participated in the study. Experimental scenarios involving 1023 training data and 105 test data, including opinion feature extraction, show that this classification model is effective in managing large and complex data. |
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Politeknik Negeri Lhokseumawe |
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2014 |
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Perpustakaan Politeknik Negeri Lhokseumawe |
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Journal of Artificial Intelligence and Software Engineering (J-AISE) |
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SOFTWARE - NETWORK ARTIFICIAL INTELLIGENCE ROBOTICS ALGORITHMS |
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KOTA LHOKSEUMAWE |
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ACEH |
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